Systems and methods for insurance underwriting

ABSTRACT

Embodiments of the present invention relate to systems and methods for automating insurance underwriting by integrating information from multiple online databases and creating decision making advice useful to insurance underwriters. One system includes a client, database, and server. The client allows an underwriter to enter applicant information, enter customized risk modifiers, and receive an underwriting decision. The database provides additional applicant information. This information can include one or more of prescription drug history, credit history, motor vehicle records, and geocentric mortality risk. The server obtains the applicant information, calculates the applicant&#39;s risk, makes an underwriting decision. Another system calculates a prescription drug risk for an applicant from pharmacy benefits management data, drug risk category data, and application data. Another system calculates a geocentric mortality risk for an applicant from census data, mortality data, credit information, and application data. Preset external modifiers are added to systems and methods of calculating risk in order to allow the underwriter to customize the risk results.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of U.S. Provisional PatentApplication Ser. No. 60/482,761, filed Jun. 27, 2003, which isincorporated herein by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

Embodiments of the present invention relate to systems and methods forinsurance underwriting. More particularly, embodiments of the presentinvention relate to systems and methods that integrate information frommultiple online databases and create decision making advice useful toinsurance underwriters.

2. Background Information

Underwriting is the process an insurance company uses to determinewhether or not a potential customer is eligible for insurance, and therate that that potential customer should pay for the insurance ifeligible. The purpose of insurance underwriting is to spread risk amonga pool of insured in a manner that is both fair to the customer andprofitable for the insurer. Like other businesses, insurance companiesneed to make a profit. Therefore, it does not make sense for them tosell term insurance, for example, to everyone who applies for it.Although they do not want to make customers pay an excessively highrate, it is not wise for them to charge all their policyholders the samepremium. Underwriting enables the company to “weed out” certainapplicants and to charge the remaining applicants premiums that arecommensurate with their level of risk.

Risk classification determines to a significant degree the premium acustomer will pay for insurance. Four typical risk groups are: standard,preferred, substandard, and uninsurable. Each of these is explainedbelow.

Standard risks: These are individuals who, according to the insurancecompany's underwriting standards, are entitled to term insurance withouthaving to pay a rating surcharge or be subjected to policy restrictions.

Preferred risks: This group includes individuals whose mortalityexperience (i.e., life expectancy) as a group is expected to be aboveaverage and to whom the company offers a lower than standard rate. Themost common preferred class today is nonsmokers, for whom many insurersnow offer a favorable rate.

Substandard risks: These are individuals who, because of their healthand/or other factors, cannot be expected (on average) to live as long aspeople who are not subject to these risk factors. Substandard applicantsare insurable, but only at higher than standard rates that reflect theadded risk. Policies issued to substandard applicants are referred to asrated or extra risk policies.

Uninsurable: These are applicants to whom the company refuses to sellterm insurance because they are unwilling to shoulder the risks. Theyhave decided that the risk factors associated with the applicant are toogreat or too numerous. In other cases, the applicant's circumstances maybe so rare or unique that the company has no basis to arrive at asuitable premium.

An insurance company typically looks at a number of factors during theunderwriting process in order to evaluate a potential customer in termsof risk. These factors enable the insurer to decide whether or not thepotential customer is insurable. If the potential customer is insurable,these factors help place them into the appropriate risk group. Some ofthe factors considered are age, sex, current health/physical condition,personal health history, family health history, financial condition,personal habits/character, occupation, and hobbies.

An insurance company will gather information about potential customersfrom several sources. In the case of term insurance, the basic source ofunderwriting information is a completed customer application. Thequestions on the application are designed to give the insurer much ofthe information needed to make a decision. The company will then eitherreject an application, accept it and offer insurance at a certain rate,or seek additional information. In many cases, the company places greatweight on the recommendations of a broker or insurance agent,particularly if the broker or agent has a good track record with thecompany. In some cases, an insurer may request a report from anindependent company that specializes in the investigation of personalmatters. This inspection report may provide the insurer with a widerange of personal information about a potential customer above andbeyond what is on the application. In addition to an inspection report,the insurer may seek information on a potential customer from one of thecooperative information bureaus the insurance industry supports. Thebest known example is the Medical Information Bureau (MIB), whichmaintains centralized files on the physical condition of individuals whohave applied for life insurance with member companies. In lifeinsurance, one of the primary factors in assessing risk is anindividual's health. Accordingly, it is no surprise that one of the mostimportant sources of underwriting information is a physical exam. Afterexamining a potential customer, a physician selected by the insurancecompany supplies the company with a detailed medical report. This reportgenerally tells the company all it needs to know about the potentialcustomer's present health.

The underwriting process is currently a manual process. It can involvenumerous people including agents and doctors, and it can be verytime-consuming. In view of the foregoing, it can be appreciated that asubstantial need exists for systems and methods that can automate theunderwriting process, improve decision-making, reduce the number ofpeople involved and speed the overall process.

BRIEF SUMMARY OF THE INVENTION

Embodiments of the present invention relate to systems and methods forautomating insurance underwriting by integrating information frommultiple online databases and creating decision making advice useful toinsurance underwriters. The first embodiment of the present invention isa system for insurance underwriting including a client, a database, anda server. The client allows information about an insurance applicantobtained from the applicant to be entered into the system and anunderwriting decision determined for the insurance applicant to bereturned from the system. The database contains information about theapplicant not obtained from the applicant. It can include but is notlimited to prescription drug histories, credit histories, motor vehiclerecords, and geocentric mortality indices. The server obtains applicantinformation entered through the client, retrieves applicant informationcontained in the database, calculates an insurance risk from theapplicant information entered through the client and the applicantinformation contained in the database, translates the insurance riskinto an underwriting decision and returns the underwriting decision tothe client. The insurance risk calculated by the server and returned tothe client may be a risk score, a risk classification, or both. Thisembodiment may further include a modifier entered into the systemthrough the client that is used by the server to modify the insurancerisk determined by the server and returned to the client.

A second embodiment is directed to a system for insurance underwritingbased on prescription drug histories. The system includes a pharmacybenefits management database, a drug risk category database, a list ofapplicant characteristics, and a processor. The pharmacy benefitsmanagement database contains a list of prescription drugs for eachindividual in the pharmacy benefits management database and informationabout each prescription drug on the list including but not limited to anational drug code, a number of individual doses dispensed, and a dateeach of the individual doses were dispensed. The drug risk categorydatabase contains prescription drugs grouped into one or more specificdisease categories that could contribute to premature death includingbut not limited to cardiovascular, cancer, smoking, hepatitis, HIVinfection, diabetes, substance abuse, pulmonary, gastrointestinal,renal, psychological, neurological, endocrine, rheumatological,musculoskeletal, hematological, and a category for drugs not fittinginto any of the other categories. The list of applicant characteristicsincludes but is not limited to one or more of sex, birth date, height,weight, and smoking status. The processor obtains an insuranceapplicant's list of prescription drugs, their dosages and dates theywere dispensed from the pharmacy benefits management database, matchesthe list of prescription drugs to disease categories from the drugcategory database, calculates a risk score for the insurance applicantbased on the disease categories matched and the list of prescriptiondrugs dosages and dates, and modifies the risk score according to thelist of applicant characteristics. This embodiment may further include asecond processor that modifies the risk score calculated by theprocessor according to a modification scheme preset externally by anunderwriter. This modification scheme may be a translation table thatthe second processor uses to translate the risk score calculated by theprocessor into a second risk score. Alternatively, this modificationscheme may be a multiplier that the second processor multiples the riskscore calculated by the processor by to produce a second risk score.

A third embodiment of the present invention is a method for calculatinga prescription drug risk score for an insurance applicant. This methodhas several steps, although it will be appreciated that two or more ofthe following steps could be collapsed into a single step, or one ormore of these steps may be broken up into even more steps. In a firststep, a list of prescription drug for the insurance applicant isobtained from a pharmacy benefits management database. The pharmacybenefits management database contains a list of prescription drugs foreach individual in the pharmacy benefits management database andinformation about each prescription drug on the list including but notlimited to a national drug code, a number of individual doses dispensed,and a date each of the individual doses were dispensed. In a secondstep, a list of characteristics of the insurance applicant is obtained.The list of characteristics of the insurance applicant includes but isnot limited to one or more of sex, birth date, height, weight, andsmoking status. In a third step, the list of drug risk categories forthe insurance applicant is obtained from a drug risk category database.The drug risk category database contains prescription drugs grouped intoone or more specific disease categories that could contribute topremature death comprising cardiovascular, cancer, smoking, HIVinfection, diabetes, substance abuse, pulmonary, hepatitis,gastrointestinal, renal, psychological, neurological, endocrine,rheumatological, musculoskeletal, hematological, and a category fordrugs not fitting into any of the other categories. In a fourth step, abody mass index of the insurance applicant is calculated from the listof characteristics and if the body mass index cannot be calculated adefault value is used. The body mass index of the insurance applicant iscalculated by dividing the weight in kilograms by the height in meterssquared. In a fifth step, the risk score of each of the drug riskcategories for the insurance applicant is set to the default no riskvalue.

In a sixth step, one or more drug risk categories and a risk score of aprescription drug are determined from the list of prescription drugs byquerying the drug risk category database with the insurance applicant'ssex and a code for the prescription drug. In a seventh step, it isdetermined if the prescription drug is a different representation of adrug already processed. This step involves comparing drugcategorization, dosage, and route of administration of the prescriptiondrug with categorization, dosage, and routes of administration of allother drugs on a list of processed prescription drugs in order todetermine if the prescription drug is a different representation of adrug already processed, discarding the prescription drug if it is adifferent representation of a drug already processed, and adding theprescription drug to the list of processed prescription drugs if it isnot a different representation of a drug already processed. In an eighthstep, it is determined if a drug category of the prescription drug issmoking. If it is, the smoking status of the insurance applicant is setto smoking. In a ninth step, a risk score of the prescription drug ismodified based on the date of dispensing. This modification involvesmultiplying the risk score of the prescription drug by a modifierspecified in a table containing different modifiers for different dateranges from the data of dispensing. In the tenth step, a risk score ofthe prescription drug is modified based on the refill pattern. Thismodification involves multiplying the risk score of the prescriptiondrug by a modifier specified in a table containing different modifiersfor different amounts of refills within different time periods.

In an eleventh step, the prescription drug is added to one or more drugrisk categories for the insurance applicant. In a twelfth step, the riskscores of each drug risk category are calculated from the risk scores ofprescription drugs in each drug risk category. This involves examiningeach prescription a drug risk category, finding a prescription drug withthe highest risk score within the drug risk category, and adding to arisk score of the prescription drug with the highest risk score withinthe drug risk category a number of unique, non-zero risk prescriptiondrugs in the drug risk category multiplied by a factor. In a thirteenthstep, the drug risk category with a highest risk score is determined. Ina fourteenth step, all prescription drugs found in the drug riskcategory with the highest risk score are removed from all other drugrisk categories to prevent biasing from multiple purpose prescriptiondrugs. The risk scores of drug categories from which prescription drugswere removed are then recalculated.

In the fifteenth step, a risk score of the drug risk category with thehighest risk score is modified according to the smoking status of theinsurance applicant and the drug risk category. One modification ismultiplying the risk score of the drug risk category with the highestrisk score by a constant if the drug risk category comprises cancer,pulmonary, cardiovascular, and diabetes and the smoking status of, theinsurance applicant comprises smoking. Another modification ismultiplying the risk score of the drug risk category with the highestrisk score by a constant if the drug risk category comprises pulmonaryand the smoking status of the insurance applicant comprises non-smoking.In a sixteenth step, a risk score of the drug risk category with thehighest risk score is modified according to the body mass index of theinsurance applicant and the drug risk category. One modification ismultiplying the risk score of the drug risk category with the highestrisk score by a constant if the drug risk category comprises cancer, HIVinfection, smoking, neurological, musculoskeletal, endocrine, andhematological and the body mass index is less than 19 and greater thanor equal to 17. A second modification is multiplying the risk score ofthe drug risk category with the highest risk score by a constant if thedrug risk category comprises psychological and the body mass index isless than 19 and greater than or equal to 17. A third modification ismultiplying the risk score of the drug risk category with the highestrisk score by a constant if the drug risk category comprisescardiovascular and diabetes and the body mass index is less than 35 andgreater than or equal to 32.

In a final step, a final prescription drug risk factor is calculated bymultiplying the individual drug score of the second and third highestrisk categories by constants and adding these values to the risk scoreof the drug risk category with the highest risk score. An exemplarycalculation involves multiplying a drug score of the second highest riskcategory by 0.5 and a drug score of the third highest risk category by0.25 and adding these values to the risk score of the drug risk categorywith the highest risk score.

This embodiment may include removing the risk contribution from thecategory for drugs not fitting into any of the other categories if thedrug risk category with the highest risk score is not the category fordrugs not fitting into any of the other categories. It may also includemodifying the final prescription drug risk by a preset external factorset by an underwriter.

A fourth embodiment of the present invention is a system for insuranceunderwriting based on geocentric mortality data. This system includes acensus database, a mortality database, a credit information database, alist of applicant characteristics, and a processor. The list ofapplicant characteristics includes but is not limited to one or more ofsex, age, income, account balances, number of accounts, credit limits,original mortgage amount, and mortgage account balance. The processorobtains population data for a region of an insurance applicant from thecensus database, gathers mortality data for the region of the insuranceapplicant from the mortality database, retrieves financial data for theregion of the insurance applicant from the credit information database,generates a mortality table for the region of the insurance applicantbased on age, sex and financial information, and calculates a geocentricmortality risk score for the insurance applicant by comparing the listof applicant characteristic with the mortality table. This embodimentmay include a second processor that modifies the geocentric mortalityrisk score calculated by the processor according to a modificationscheme preset externally by an underwriter.

A fifth embodiment of the present invention is method for calculating ageocentric mortality risk score for an insurance applicant. This methodalso has, several steps. In a first step, a table containing populationsof a region in which the insurance applicant lives grouped by age andsex is obtained. In a second step, a table containing the number ofdeaths that have occurred in the region in which the insurance applicantlives grouped by age and sex is obtained. In a third step, a tablecontaining the financial data of households in the region in which theinsurance applicant lives grouped by age and sex is obtained. In afourth step, a mortality table for the region in which the insuranceapplicant lives based on financial data, age, and sex is generated. In afifth step, a list of applicant characteristics about the insuranceapplicant is obtained. The list of applicant characteristics includesbut is not limited to one or more of sex, age, income, account balances,number of accounts, credit limits, original mortgage amount, andmortgage account balance. In a sixth step, a geocentric mortality riskscore is calculated by comparing the list of applicant characteristicsto the mortality table. This embodiment may include an additional stepof modifying the geocentric mortality risk score by a preset externalfactor set by an underwriter.

A sixth embodiment of the present invention is a system for insuranceunderwriting. The system includes but is not limited to a firstprocessor that determines prescription drug risk, a second processorthat determines geocentric mortality risk, a third processor thatdetermines motor vehicle records risk, a fourth processor thatdetermines credit information risk, a list of risks based on anapplicant's application information, and a fifth processor. The fifthprocessor calculates an overall risk score by combining one or more ofthe risk scores of the first processor, the second processor, the thirdprocessor, the fourth processor, and the risks based on an applicant'sapplication information. This embodiment may also contain a translationtable used by the fifth processor to translate the risk scores of thefirst processor, the second processor, the third processor, the fourthprocessor and the risks based on an applicant's application informationbased on preset external factors set by the underwriter.

A seventh embodiment of the present invention is a method forcalculating overall risk for an insurance applicant. In a first step, afirst risk score is calculated based on a prescription drug history ofthe insurance applicant. In a second step, a second risk score for theinsurance applicant is calculated based on a geocentric mortality data.In a third step, a third risk score is calculated based on a motorvehicle report history of the insurance applicant. In a fourth step, afourth risk score is calculated based on a credit report for theinsurance applicant. In a fifth step, additional risk parameters fromthe application data of the insurance applicant are gathered. In a finalstep, the overall risk for the insurance applicant is generated bycombining one or more of the first risk score, the second risk score,the third risk score, the fourth risk score, and the additional riskparameters. This embodiment may also include the additional step ofmodifying the first risk score, the second risk score, the third risk,the fourth risk score, and the additional risk parameters based on atranslation table provided as preset external data from an underwriter.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram showing two paths of communication betweena client and a server in an insurance underwriting system containing aclient, a database, and a server in accordance with an embodiment of thepresent invention.

FIG. 2 is a schematic diagram showing three paths of communicationbetween a client and a server in an insurance underwriting systemcontaining a client, a database, and a server in accordance with anembodiment of the present invention.

FIG. 3 is schematic diagram of a system for insurance underwriting basedon prescription drug histories in accordance with an embodiment of thepresent invention.

FIG. 4 is schematic diagram of a system for insurance underwriting basedon prescription drug histories including a second processor thatmodifies the original risk score in accordance with an embodiment of thepresent invention.

FIG. 5 is a flowchart showing a first series of steps of a method forcalculating a prescription drug risk score for an insurance applicant inaccordance with an embodiment of the present invention.

FIG. 6 is a flowchart showing a second series of steps of a method forcalculating a prescription drug risk score for an insurance applicant inaccordance with an embodiment of the present invention.

FIG. 7 is schematic diagram of a system for insurance underwriting basedon geocentric mortality data in accordance with an embodiment of thepresent invention.

FIG. 8 is schematic diagram of a system for insurance underwriting basedon geocentric mortality data including a second processor in accordancewith an embodiment of the present invention.

FIG. 9 is a flowchart showing a method for calculating a geocentricmortality risk score for an insurance applicant in accordance with anembodiment of the present invention.

FIG. 10 is schematic diagram of a system for insurance underwritingbased on prescription drug risk, geocentric mortality risk, motorvehicle records risk, credit information risk, and risks based on anapplicant's application information in accordance with an embodiment ofthe present invention.

FIG. 11 is schematic diagram of a system for insurance underwritingbased on prescription drug risk, geocentric mortality risk, motorvehicle records risk, credit information risk, risks based on anapplicant's application information, and a translation table inaccordance with an embodiment of the present invention.

FIG. 12 is a flowchart of a method for calculating overall risk for aninsurance applicant based on prescription drug risk, geocentricmortality risk, motor vehicle records risk, credit information risk, andrisks based on an applicant's application information in accordance withan embodiment of the present invention.

Before one or more embodiments of the invention are described in detail,one skilled in the art will appreciate that the invention is not limitedin its application to the details of construction, the arrangements ofcomponents, and the arrangement of steps set forth in the followingdetailed description or illustrated in the drawings. The invention iscapable of other embodiments and of being practiced or being carried outin various ways. Also, it is to be understood that the phraseology andterminology used herein is for the purpose of description and should notbe regarded as limiting.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic diagram showing two paths of communication betweena client and a server in an insurance underwriting system containing aclient, a database, and a server in accordance with an embodiment of thepresent invention. In underwriting system 100, client 110 allowsinformation about an insurance applicant obtained from the applicant tobe entered into system 100. Exemplary methods of obtaining thisinformation include an agent or underwriter receiving it orally from theapplicant and entering it into system 100, an agent or underwritertranscribing it from a written application into system 100, or applicantentering the data directly where system 100 is an online system. In thethese examples, the users of client 110 are an agent, an underwriter, oran applicant. This information is sent from client 110 to server 120 forprocessing via communications path 130. Client 110 also receives outputfrom the system. This output is in the form of an underwriting decisiondetermined by server 120 for the insurance applicant. An underwritingdecision is the decision to write a policy for the applicant, to notwrite a policy for the applicant, or to refer the applicant to anotherunderwriting process. The underwriting decision determined by server 120for the insurance applicant is sent to client 110 via communicationspath 140.

Database 150 contains information about the applicant not obtained fromthe applicant. This information can include but is not limited toprescription drug histories, credit histories, motor vehicle records,and geocentric mortality indices. Database 150 is used to gatheradditional information about an applicant and to verify informationalready known about an applicant. Server 120 queries database 150 andreceives this information via communications path 160.

Server 120 is the processor of underwriting system 100. Server 120obtains applicant information entered through client 110. It retrievesapplicant information contained in database 150. It calculated theinsurance risk of the applicant from the applicant information enteredthrough client 110 and the applicant information contained in database140. Exemplary insurance risks provided by underwriting systems includea risk score and a risk classification. A risk score is a numeric valuewithin a numeric range of risk. A risk classification is a grouping ofapplicants based on risk, as was described earlier. Server 120translates the insurance risk into an underwriting decision. Anexemplary server 120 translates a risk score into an underwritingdecision by calling one range of risk scores a decision to underwrite apolicy, a second range of risks scores a decision to refer the applicantto traditional underwriting, and a third range of risk scores a decisionnot to underwrite a policy. Similarly, an exemplary server 120translates a risk classification through the use of a lookup table. Foran uninsurable classification the underwriting decision is not to writea policy. For classifications substandard to preferred the decision isto underwrite the policy but at decreasing premiums for each of theclassifications. Finally, server 120 returns the underwriting decisionto client 110.

The method used by server 120 to determine the insurance risk variesdepending on the database used. Also, if more than one database 150 isused, server 120 calculates the risk according to each database 150 andthen calculates an overall insurance risk for the applicant. The use ofone or many databases is under the control of the underwriter or agentin system 100. The underwriter or agent can then explore more than onescenario utilizing one or more databases. Server 120 then provides atype of programming interface for the underwriting process. When system100 is configured as an online system to be accessed by applicants, theuse of one or more databases is preset or varied according theinformation provided by the applicant.

FIG. 2 is a schematic diagram showing three paths of communicationbetween a client and a server in an insurance underwriting systemcontaining a client, a database, and a server in accordance with anembodiment of the present invention. In system 200, client 110 allows amodifier to be entered into the system that will modify the insurancerisk determined by server 120 and returned to client 110. This modifieris entered via communication path 210. An exemplary modifier is amultiplier that is multiplied by the risk score to change its value.Another exemplary modifier is a translation table. A translation tableis used to change the value of risk scores within a certain range to aspecified value. Modifiers are used by underwriters to customize theunderwriting results according to their experience. They are also usedto enable the results to match the input parameters of other automatedsystems. If one or more databases 150 are used, then one or moremodifiers are entered into the system through client 110. Communicationspaths 130, 140, 160, and 210 provide data communications via one or morecomputer networks.

FIG. 3 is schematic diagram of a system for insurance underwriting basedon prescription drug histories in accordance with an embodiment of thepresent invention. System 300 includes pharmacy benefits management(PBM) database 310, drug risk category database 320, list of applicantcharacteristics 330, and prescription drug underwriting processor 340.PBM database 310 contains a list of prescription drugs for eachindividual in PBM database 310. It also includes information about eachprescription drug on the list including but not limited to a nationaldrug code, a number of individual doses dispensed, and a date each ofthe individual doses were dispensed. Drug risk category database 320contains prescription drugs grouped into one or more specific diseasecategories that could contribute to premature death. These categoriesinclude but are not limited to cardiovascular, cancer, smoking,hepatitis, HIV infection, diabetes, substance abuse, pulmonary,gastrointestinal, renal, psychological, neurological, endocrine,rheumatological, musculoskeletal, hematological, and a category fordrugs not fitting into any of the other categories. List of applicantcharacteristics 330 contains information about the applicant obtainedfrom the applicant. This information is obtained during the applicationprocess and includes but is not limited to one or more of sex, birthdate, height, weight, and smoking status. Processor 340 retrieves aninsurance applicant's list of prescription drugs, their dosages anddates they were dispensed from the pharmacy benefits managementdatabase. It matches the list of prescription drugs to diseasecategories from drug category database 320. It calculates a risk scorefor the insurance applicant based on the disease categories matched andthe list of prescription drugs dosages and dates dispensed. Finally, itmodifies the risk score according to the list of applicantcharacteristics to produce the prescription drug risk score 350.

FIG. 4 is schematic diagram of a system for insurance underwriting basedon prescription drug histories including a second processor thatmodifies the original risk score in accordance with an embodiment of thepresent invention. In system 400, a second processor 410 modifies therisk score calculated by the processor 340 according to a modificationscheme preset externally by an underwriter. This modification scheme maybe a translation table that second processor 410 uses to translate therisk score calculated by processor 340 into a second risk score.Alternatively, this modification scheme may be a multiplier that secondprocessor 410 multiples the risk score calculated by processor 340 by toproduce second risk score 420.

FIG. 5 is a flowchart showing a first series of steps of a method forcalculating a prescription drug risk score for an insurance applicant inaccordance with an embodiment of the present invention. A series ofsteps will be described with respect to this method, but those skilledin the art will appreciate that some of these steps may be combined orfurther broken down into yet additional steps.

In step 501 of method 500, a list of prescription drugs for theinsurance applicant is obtained from a pharmacy benefits managementdatabase. The pharmacy benefits management database contains a list ofprescription drugs for each individual in the pharmacy benefitsmanagement database and information about each prescription drug on thelist including but not limited to a national drug code, a number ofindividual doses dispensed, and a date each of the individual doses weredispensed.

In step 502, a list of characteristics of the insurance applicant isobtained. The list of characteristics of the insurance applicantincludes but is not limited to one or more of sex, birth date, height,weight, and smoking status.

In step 503, the list of drug risk categories for the insuranceapplicant is obtained from a drug risk category database. The drug riskcategory database contains prescription drugs grouped into one or morespecific disease categories that could contribute to premature deathcomprising cardiovascular, cancer, smoking, HIV infection, diabetes,substance abuse, pulmonary, hepatitis, gastrointestinal, renal,psychological, neurological, endocrine, rheumatological,musculoskeletal, hematological, and a category for drugs not fittinginto any of the other categories.

In step 504, a body mass index of the insurance applicant is calculatedfrom the list of characteristics and if the body mass index cannot becalculated a default value is used. An exemplary default value is 25.The body mass index of the insurance applicant is calculated by dividingthe weight in kilograms by the height in meters squared.

In step 505, the risk score of each of the drug risk categories for theinsurance applicant is set to the default no risk value. This is aninitialization step since the drug risk categories are used later tocalculate the final risk value.

In step 506, one or more drug risk categories and a risk score of aprescription drug are determined from the list of prescription drugs byquerying the drug risk category database with the insurance applicant'ssex and a code for the prescription drug. The national drug code of eachprescription drug is used to query the drug risk category database. Thedatabase is also segregated with respect to gender, so the sex of theapplicant is also used in the query. From querying the drug riskcategory database the initial risk score of each drug is found. Thecategory or categories to which each prescription drug belongs is alsodetermined. The list of drug risk categories includes but is not limitedto cardiovascular, cancer, smoking, hepatitis, HIV infection, diabetes,substance abuse, pulmonary, gastrointestinal, renal, psychological,neurological, endocrine, rheumatological, musculoskeletal,hematological, and a category for drugs not fitting into any of theother categories. Exemplary risk values for a prescription are from arange between 0 and 90 and including 0 and 90, where 0 is no risk and 90is the highest risk possible for a single drug.

In step 507, it is determined if the prescription drug is a differentrepresentation of a drug already processed. Obviously, drugs with thesame national drug code are the same drug, but different manufacturersand especially generic drugs may be identical, yet have different codes.This step involves comparing drug categorization, dosage, and route ofadministration of the prescription drug with categorization, dosage, androutes of administration of all other drugs on a list of processedprescription drugs in order to determine if the prescription drug is adifferent representation of a drug already processed. A prescriptiondrug is discarded if it is a different representation of a drug alreadyprocessed. Drugs not already processed are added to the list ofprocessed prescription drugs.

In step 508, it is determined if a drug category of the prescriptiondrug is smoking. If it is, the smoking status of the insurance applicantis set to smoking. Exemplary values for the smoking status of anapplicant include smoking, non-smoking, and prior smoking.

FIG. 6 is a flowchart showing a second series of steps of a method forcalculating a prescription drug risk score for an insurance applicant inaccordance with an embodiment of the present invention.

In step 509 of method 500, a risk score of the prescription drug ismodified based on the date of dispensing. This modification involvesmultiplying the risk score of the prescription drug by a modifierspecified in a table containing different modifiers for different dateranges from the data of dispensing. An exemplary modifier for aprescription drug not dispensed in the past two years is 0.50. Anexemplary modifier for a prescription drug dispensed within the past twoyears is 0.75.

In the step 510, a risk score of the prescription drug is modified basedon the refill pattern. This modification involves multiplying the riskscore of the prescription drug by a modifier specified in a tablecontaining different modifiers for different amounts of refills withindifferent time periods. An exemplary modifier for a prescription drugwith up to 6 refills in a two year period is 0.75. An exemplary modifierfor a prescription drug with between 6 and 12 refills in a two yearperiod is 0.75.

In step 511, the prescription drug is added to one or more drug riskcategories for the insurance applicant.

In step 512, the risk scores of each drug risk category are calculatedfrom the risk scores of prescription drugs in each drug risk category.This involves examining each prescription a drug risk category andfinding the prescription drug with the highest risk score within thedrug risk category. The risk score of the drug risk category is thencalculated by counting the other of unique, non-zero risk prescriptiondrugs in the drug risk category, multiplying this count by a factor, andadding this value to the risk score of the prescription drug with thehighest risk score within the drug risk category.

In step 513, the drug risk category with a highest risk score isdetermined. This is determined by comparing the risk scores of all thedrug risk categories for the applicant.

In step 514, all prescription drugs found in the drug risk category withthe highest risk score are removed from all other drug risk categoriesto prevent biasing from multiple purpose prescription drugs. The riskscores of drug categories from which prescription drugs were removed arethen recalculated.

In step 515, a risk score of the drug risk category with the highestrisk score is modified according to the smoking status of the insuranceapplicant and the drug risk category. One modification is multiplyingthe risk score of the drug risk category with the highest risk score bya constant if the drug risk category comprises cancer, pulmonary,cardiovascular, and diabetes and the smoking status of the insuranceapplicant comprises smoking. Another modification is multiplying therisk score of the drug risk category with the highest risk score by aconstant if the drug risk category comprises pulmonary and the smokingstatus of the insurance applicant comprises non-smoking.

In step 516, a risk score of the drug risk category with the highestrisk score is modified according to the body mass index of the insuranceapplicant and the drug risk category. One modification is multiplyingthe risk score of the drug risk category with the highest risk score bya constant if the drug risk category comprises cancer, HIV infection,smoking, neurological, musculoskeletal, endocrine, and hematological andthe body mass index is less than 19 and greater than or equal to 17. Asecond modification is multiplying the risk score of the drug riskcategory with the highest risk score by a constant if the drug riskcategory comprises psychological and the body mass index is less than 19and greater than or equal to 17. A third modification is multiplying therisk score of the drug risk category with the highest risk score by aconstant if the drug risk category comprises cardiovascular and diabetesand the body mass index is less than 35 and greater than or equal to 32.

In step 517, a final prescription drug risk factor is calculated bymultiplying the individual drug score of the second and third highestrisk categories by constants and adding these values to the risk scoreof the drug risk category with the highest risk score. An exemplarycalculation involves multiplying a drug score of the second highest riskcategory by 0.5 and a drug score of the third highest risk category by0.25 and adding these values to the risk score of the drug risk categorywith the highest risk score.

Method 500 can include a number of additional steps. One step ismodifying a risk score of the prescription drug based on a dosagepattern. This involves multiplying the risk score of the prescription bya modifier specified in a table containing different modifiers fordifferent dosages of the prescription drug. An exemplary dosagemultiplier is 0.70 for a very low dose. Another exemplary multiplier is0.90 for a high dose.

Another additional step is removing the risk contribution from thecategory for drugs not fitting into any of the other categories, if thedrug risk category with the highest risk score is not the category fordrugs not fitting into any of the other categories.

A final additional step is modifying the final prescription drug risk bya preset external factor set by an underwriter.

FIG. 7 is schematic diagram of a system for insurance underwriting basedon geocentric mortality data in accordance with an embodiment of thepresent invention. System 700 includes census database 710, mortalitydatabase 720, credit information database 730, a list of applicantcharacteristics 740, and geocentric mortality processor 750. List ofapplicant characteristics 740 includes but is not limited to one or moreof sex, age, income, account balances, number of accounts, creditlimits, original mortgage amount, and mortgage account balance.Processor 750 obtains population data for a region of an insuranceapplicant from the census database. It gathers mortality data for theregion of the insurance applicant from the mortality database. Itretrieves financial data for the region of the insurance applicant fromthe credit information database. It generates a mortality table for theregion of the insurance applicant based on age, sex and financialinformation. Finally, it calculates geocentric mortality risk score 760for the insurance applicant by comparing the list of applicantcharacteristic with the mortality table.

FIG. 8 is schematic diagram of a system for insurance underwriting basedon geocentric mortality data including a second processor in accordancewith an embodiment of the present invention. System 800 includes secondprocessor 810 that modifies the geocentric mortality risk scorecalculated by processor 750 according to a modification scheme presetexternally by an underwriter. System 800 then produced modifiedgeocentric mortality risk score 820.

FIG. 9 is a flowchart showing a method for calculating a geocentricmortality risk score for an insurance applicant in accordance with anembodiment of the present invention.

In step 910, a table containing populations of a region in which theinsurance applicant lives grouped by age and sex is obtained.

In the step 920, a table containing the number of deaths that haveoccurred in the region in which the insurance applicant lives grouped byage and sex is obtained.

In the step 930, a table containing the financial data of households inthe region in which the insurance applicant lives grouped by age and sexis obtained.

In step 940, a mortality table for the region in which the insuranceapplicant lives based on financial data, age, and sex is generated.

In step 950, a list of applicant characteristics about the insuranceapplicant is obtained. The list of applicant characteristics includesbut is not limited to one or more of sex, age, income, account balances,number of accounts, credit limits, original mortgage amount, andmortgage account balance.

In step 960, a geocentric mortality risk score is calculated bycomparing the list of applicant characteristics to the mortality table.

An additional step for method 900 is modifying the geocentric mortalityrisk score by a preset external factor set by an underwriter. This stepallows the underwriter to customize the results of the method.

FIG. 10 is schematic diagram of a system for insurance underwritingbased on prescription drug risk, geocentric mortality risk, motorvehicle records risk, credit information risk, and risks based on anapplicant's application information in accordance with an embodiment ofthe present invention. System 1000, includes but is not limited to firstprocessor 1010 that determines prescription drug risk, a secondprocessor 1020 that determines geocentric mortality risk, a thirdprocessor 1030 that determines motor vehicle records risk, a fourthprocessor 1040 that determines credit information risk, list of risksbased on an applicant's application information 1050, and fifthprocessor 1060. Exemplary motor vehicle records risk is calculated basedon violations or accidents. Exemplary credit information risk iscalculated based on net worth, outstanding loans, account balances, orunpaid bills. Exemplary risks based on an applicant's applicationinformation include occupation, avocation, and whether or not theapplicant is a smoker. Fifth processor 1060 calculates overall riskscore 1070 by combining one or more of the risk scores of the firstprocessor 1010, second processor 1020, third processor 1030, fourthprocessor 1040, and list of risks based on an applicant's applicationinformation 1050. An exemplary method of combining the risk scores is toadd them with or without first applying weighting factors.

FIG. 11 is schematic diagram of a system for insurance underwritingbased on prescription drug risk, geocentric mortality risk, motorvehicle records risk, credit information risk, risks based on anapplicant's application information, and a translation table inaccordance with an embodiment of the present invention. System 1100contains translation table 1110 used by fifth processor 1060 totranslate the risk scores of the first processor, the second processor,the third processor, the fourth processor and the risks based on anapplicant's application information based on preset external factors setby the underwriter. System 1100 then produces modified overall riskscore 1120. An exemplary translation table translates a prescriptiondrug risk in the range 41 to 45, to 100. In this way, an individualprocessor's range of 0 to 90 can be converted to an overall risk rangeof 0 to 250, for example.

FIG. 12 is a flowchart of a method for calculating overall risk for aninsurance applicant based on prescription drug risk, geocentricmortality risk, motor vehicle records risk, credit information risk, andrisks based on an applicant's application information in accordance withan embodiment of the present invention.

In step 1210, a first risk score is calculated based on a prescriptiondrug history of the insurance applicant.

In step 1220, a second risk score for the insurance applicant iscalculated based on a geocentric mortality data.

In step 1230, a third risk score is calculated based on a motor vehiclereport history of the insurance applicant.

In step 1240, a fourth risk score is calculated based on a credit reportfor the insurance applicant.

In step 1250, additional risk parameters from the application data ofthe insurance applicant are gathered.

In step 1260, the overall risk for the insurance applicant is generatedby combining one or more of the first risk score, the second risk score,the third risk score, the fourth risk score, and the additional riskparameters.

An additional step of method 1200 is modifying the first risk score, thesecond risk score, the third risk, the fourth risk score, and theadditional risk parameters based on a translation table provided aspreset external data from an underwriter.

Systems and methods in accordance with embodiments of the presentinvention disclosed herein can advantageously improve the speed ofinsurance underwriting and reduce the overall cost. Such systems andmethods also provide agents and underwriters with a customizable toolthat can be used to explore different underwriting scenarios.

The foregoing disclosure of the preferred embodiments of the presentinvention has been presented for purposes of illustration anddescription. It is not intended to be exhaustive or to limit theinvention to the precise forms disclosed. Many variations andmodifications of the embodiments described herein will be apparent toone of ordinary skill in the art in light of the above disclosure. Thescope of the invention is to be defined only by the claims appendedhereto, and by their equivalents.

Further, in describing representative embodiments of the presentinvention, the specification may have presented the method and/orprocess of the present invention as a particular sequence of steps.However, to the extent that the method or process does not rely on theparticular order of steps set forth herein, the method or process shouldnot be limited to the particular sequence of steps described. As one ofordinary skill in the art would appreciate, other sequences of steps maybe possible. Therefore, the particular order of the steps set forth inthe specification should not be construed as limitations on the claims.In addition, the claims directed to the method and/or process of thepresent invention should not be limited to the performance of theirsteps in the order written, and one skilled in the art can readilyappreciate that the sequences may be varied and still remain within thespirit and scope of the present invention.

1. A system for insurance underwriting, comprising: at least onedatabase containing information about an insurance applicant, whereinthe information about the insurance applicant includes insuranceapplication information obtained from the insurance applicant andadditional information not obtained from the insurance applicant,wherein the additional information not obtained from the insuranceapplicant comprises a plurality of prescription drugs dispensed to theinsurance applicant; a drug risk category database that groups theplurality of prescription drugs dispensed to the insurance applicantwithin a drug risk category; and a server in communication with the atleast one database and a client computer used to enter the insuranceapplication information obtained from the insurance applicant, whereinthe server is configured to: retrieve the insurance applicationinformation obtained from the insurance applicant and the additionalinformation not obtained from the insurance applicant from the database;determine a plurality of risk scores for the insurance applicant fromthe insurance application information and the additional informationretrieved from the database, wherein the plurality of risk scoresinclude an initial prescription drug risk score, a geocentric mortalityrisk score, a motor vehicle records risk score, and a credit informationrisk score; modify at least the initial prescription drug risk scoreaccording to a predetermined modification scheme established by anexternal underwriter, wherein to modify the initial prescription drugrisk score according to the predetermined modification scheme, theserver is further configured to: determine a plurality of risk scoresfor the plurality of prescription drugs grouped within the drug riskcategory, wherein the server identifies one of the plurality ofprescription drugs grouped within the drug risk category having ahighest risk score; multiply a remaining number of the plurality ofprescription drugs grouped within the drug risk category having unique,non-zero risk scores by a predetermined factor; and add the highest riskscore associated with the identified prescription drug to a valueobtained from multiplying the remaining number of the plurality ofprescription drugs by the predetermined factor, wherein the server addsthe highest risk score and the obtained value to calculate a risk scorefor the drug risk category, and wherein the server modifies the initialprescription drug score based on the risk score calculated for the drugrisk category; calculate an overall risk score for the insuranceapplicant, wherein the server combines the modified prescription drugrisk score with one or more of the geocentric mortality risk score, themotor vehicle records risk score, or the credit information risk scoreto calculate the overall risk score for the insurance applicant;translate the overall risk score into an insurance underwriting decisionfor the insurance applicant; and return the insurance underwritingdecision for the insurance applicant to the client computer.
 2. Thesystem of claim 1, wherein the additional information in the at leastone database not obtained from the insurance applicant comprises one ormore of a prescription drug history, a credit history, a motor vehiclerecord, or a geocentric mortality index.
 3. The system of claim 1,wherein the insurance underwriting decision comprises a decision tounderwrite an insurance policy for the insurance applicant in responseto the overall risk score having a numeric value within a first numericrisk range, a decision to refer to the insurance applicant totraditional underwriting in response to the overall risk score having anumeric value within a second numeric risk range, and a decision to notunderwrite the insurance policy for the insurance applicant in responseto the overall risk score having a numeric value within a third numericrisk range.
 4. The system of claim 1, wherein the server is furtherconfigured to modify the overall risk score calculated for the insuranceapplicant according to the predetermined modification scheme establishedby the external underwriter.
 5. A system for insurance underwriting,comprising: at least one database containing information about aninsurance applicant, wherein the information about the insuranceapplicant includes insurance application information obtained from theinsurance applicant and additional information not obtained from theinsurance applicant, wherein the additional information not obtainedfrom the insurance applicant comprises a plurality of prescription drugsdispensed to the insurance applicant; a drug risk category database thatgroups the plurality of prescription drugs dispensed to the insuranceapplicant within a drug risk category; a first processor configured todetermine an initial prescription drug risk score for the insuranceapplicant from the insurance application information in the database; asecond processor configured to determine a geocentric mortality riskscore for the insurance applicant from the insurance applicationinformation in the database; a third processor configured to determine amotor vehicle records risk score for the insurance applicant from theinsurance application information in the database; a fourth processorconfigured to determine a credit information risk score for theinsurance applicant from the insurance application information in thedatabase; and a fifth processor configured to: modify at least theinitial prescription drug risk score according to a predeterminedmodification scheme established by an external underwriter, wherein tomodify the initial prescription drug risk score according to thepredetermined modification scheme, the fifth processor is furtherconfigured to: determine a plurality of risk scores for the plurality ofprescription drugs grouped within the drug risk category, wherein thefifth processor identifies one of the plurality of prescription drugsgrouped within the drug risk category having a highest risk score;multiply a remaining number of the plurality of prescription drugsgrouped within the drug risk category having unique, non-zero riskscores by a predetermined factor; and add the highest risk scoreassociated with the identified prescription drug to a value obtainedfrom multiplying the remaining number of the plurality of prescriptiondrugs by the predetermined factor, wherein the fifth processor adds thehighest risk score and the obtained value to calculate a risk score forthe drug risk category, and wherein the fifth processor modifies theinitial prescription drug score based on the risk score calculated forthe drug risk category; combine the modified prescription drug riskscore with one or more of the geocentric mortality risk score, the motorvehicle records risk score, or the credit information risk score tocalculate an overall risk score for the insurance applicant; translatethe overall risk score into an insurance underwriting decision for theinsurance applicant.
 6. The system of claim 5, wherein the insuranceunderwriting decision comprises a decision to underwrite an insurancepolicy for the insurance applicant in response to the overall risk scorehaving a numeric value within a first numeric risk range, a decision torefer to the insurance applicant to traditional underwriting in responseto the overall risk score having a numeric value within a second numericrisk range, and a decision to not underwrite the insurance policy forthe insurance applicant in response to the overall risk score having anumeric value within a third numeric risk range.
 7. A method forinsurance underwriting, comprising: storing information about aninsurance applicant in at least one database, wherein the informationabout the insurance applicant includes insurance application informationobtained from the insurance applicant; storing additional informationabout the insurance applicant not obtained from the insurance applicantin a drug risk category database, wherein the additional information notobtained from the insurance applicant includes a plurality ofprescription drugs dispensed to the insurance applicant, and wherein thedrug risk category database groups the plurality of prescription drugsdispensed to the insurance applicant within a drug risk category;determining, on a computer server, an initial prescription drug riskscore for the insurance applicant from a prescription drug historyassociated with the insurance application information obtained from theinsurance applicant and stored in the database; determining, on thecomputer server, a geocentric mortality risk score for the insuranceapplicant from geocentric mortality data associated with the insuranceapplication information obtained from the insurance applicant and storedin the database; determining, on the computer server, a motor vehiclerecords risk score for the insurance applicant from a motor vehiclereport history associated with the insurance application informationobtained from the insurance applicant and stored in the database;determining, on the computer server, a credit information risk score forthe insurance applicant from a credit report associated with theinsurance application information obtained from the insurance applicantand stored in the database; modifying, on the computer server, at leastthe initial prescription drug risk score according to a predeterminedmodification scheme established by an external underwriter, whereinmodifying the initial prescription drug risk score according to thepredetermined modification scheme includes: determining, on the computerserver, a plurality of risk scores for the plurality of prescriptiondrugs grouped within the drug risk category, wherein the computer serveridentifies one of the plurality of prescription drugs grouped within thedrug risk category having a highest risk score; multiplying, on thecomputer server, a remaining number of the plurality of prescriptiondrugs grouped within the drug risk category having unique, non-zero riskscores by a predetermined factor; and adding, on the computer server,the highest risk score associated with the identified prescription drugto a value obtained from multiplying the remaining number of theplurality of prescription drugs by the predetermined factor, wherein thecomputer server adds the highest risk score and the obtained value tocalculate a risk score for the drug risk category, and wherein thecomputer server modifies the initial prescription drug score based onthe risk score calculated for the drug risk category; calculating, onthe computer server, an overall risk score for the insurance applicant,wherein calculating the overall risk score for the insurance applicantincludes combining the modified prescription drug risk score with one ormore of the geocentric mortality risk score, the motor vehicle recordsrisk score, or the credit information risk score; and translating theoverall risk score into an insurance underwriting decision for theinsurance applicant.
 8. The method of claim 7, wherein the insuranceunderwriting decision comprises a decision to underwrite an insurancepolicy for the insurance applicant in response to the overall risk scorehaving a numeric value within a first numeric risk range, a decision torefer to the insurance applicant to traditional underwriting in responseto the overall risk score having a numeric value within a second numericrisk range, and a decision to not underwrite the insurance policy forthe insurance applicant in response to the overall risk score having anumeric value within a third numeric risk range.
 9. The system of claim1, wherein the additional information in the at least one database notobtained from the insurance applicant comprises at least oneprescription drug dispensed to the insurance applicant.
 10. The systemof claim 9, wherein the server is further configured to query the drugrisk category database with a gender for the insurance applicant and anational drug code for the prescription drug dispensed to the insuranceapplicant, wherein the server queries the drug risk category databasewith the gender for the insurance applicant and the national drug codefor the prescription drug dispensed to the insurance applicant todetermine the initial prescription drug risk score for the insuranceapplicant.
 11. The system of claim 10, wherein the server is furtherconfigured to: determine a date when the prescription drug was dispensedto the insurance applicant, wherein the server determines the date whenthe prescription drug was dispensed to the insurance applicant toidentify a date range modifier in the predetermined modification; andmultiply the initial prescription drug risk score by the identified daterange modifier, wherein the modified prescription drug risk scorecomprises the initial prescription drug risk score multiplied by theidentified date range modifier.
 12. The system of claim 10, wherein theserver is further configured to: determine a number of refills dispensedto the insurance applicant for the prescription drug, wherein the serverdetermines the number of refills dispensed to the insurance applicant toidentify a refill pattern modifier in the predetermined modification;and multiply the initial prescription drug risk score by the identifiedrefill pattern modifier, wherein the modified prescription drug riskscore comprises the initial prescription drug risk score multiplied bythe identified refill pattern modifier.
 13. The system of claim 10,wherein the server is further configured to: determine a dosage for theprescription drug dispensed to the insurance applicant, wherein theserver determines the dosage for the prescription drug to identify adosage pattern modifier in the predetermined modification scheme; andmultiply the initial prescription drug risk score by the identifieddosage pattern modifier, wherein the modified prescription drug riskscore comprises the initial prescription drug risk score multiplied bythe identified dosage pattern modifier.
 14. The system of claim 9,wherein the server is further configured to: query a drug risk categorydatabase with a national drug code for the prescription drug dispensedto the insurance applicant, wherein the drug risk category databasegroups a plurality of prescription drugs into a plurality of diseasecategories that could contribute to premature death; and determine adrug risk category for the prescription drug dispensed to the insuranceapplicant from one or more of the plurality of disease categoriesmatching the prescription drug dispensed to the insurance applicant. 15.The system of claim 14, wherein the server is further configured toassign a smoking status to the insurance applicant in response to thedetermined drug risk category comprising a smoking drug risk category.16. The system of claim 1, wherein one or more of the initialprescription drug risk score or the modified prescription drug riskscore are based on the risk score calculated for the drug risk category.17. The system of claim 1, wherein the additional information in the atleast one database not obtained from the insurance applicant comprises aplurality of prescription drugs dispensed to the insurance applicant,and wherein a drug risk category database groups the plurality ofprescription drugs dispensed to the insurance applicant within aplurality of drug risk categories.
 18. The system of claim 17, whereinthe server is further configured to: determine that the plurality ofprescription drugs dispensed to the insurance applicant include multipledifferent representations of one prescription drug; and discard all butone of the multiple different representations of the one prescriptiondrug from the plurality of prescription drugs dispensed to the insuranceapplicant.
 19. The system of claim 17, wherein the server is furtherconfigured to calculate a plurality of initial risk scores for theplurality of drug risk categories that group the plurality ofprescription drugs dispensed to the insurance applicant, wherein theserver identifies one of the plurality of drug risk categories having ahighest initial risk score.
 20. The system of claim 19, wherein theserver is further configured to: identify any of the plurality ofprescription drugs grouped within the identified drug risk categoryhaving the highest initial risk score that are further grouped withinother ones of the plurality of drug risk categories; and remove theidentified prescription drugs from the other drug risk categories,wherein the server remove the identified prescription drugs from theother drug risk categories to prevent biasing from multiple purposeprescription drugs.
 21. The system of claim 19, wherein the server isfurther configured to: determine a smoking status assigned to theinsurance applicant, wherein the server determines the smoking statusassigned to the insurance applicant to identify a smoking constant inthe predetermined modification scheme; and multiply the initial riskscore associated with the drug risk category having the highest initialrisk score by the identified smoking constant, wherein the modifiedprescription drug risk score comprises the initial risk score associatedwith the drug risk category having the highest initial risk scoremultiplied by the identified smoking constant.
 22. The system of claim19, wherein the server is further configured to: determine a weight inkilograms and a height in meters for the insurance applicant from theinsurance application information obtained from the insurance applicant;calculate a body mass index for the insurance applicant from the weightin kilograms and the height in meters determined for the insuranceapplicant, wherein the calculated body mass index includes the weight inkilograms divided by the height in meters squared; identify a body massindex constant in the predetermined modification scheme from the bodymass index calculated for the insurance applicant; and multiply theinitial risk score associated with the drug risk category having thehighest initial risk score by the identified body mass index constant,wherein the modified prescription drug risk score comprises the initialrisk score associated with the drug risk category having the highestinitial risk score multiplied by the identified body mass indexconstant.
 23. The system of claim 19, wherein the server is furtherconfigured to: identify one of the plurality of drug risk categorieshaving a second highest initial risk score and one of the plurality ofdrug risk categories having a third highest initial risk score; multiplythe second highest initial risk score by a first constant; multiply thethird highest initial risk score by a second constant, wherein thesecond constant comprises a lower value than the first constant; and addthe highest initial risk score to the second highest initial risk scoremultiplied by the first constant and the third highest initial riskscore multiplied by the second constant, wherein the modifiedprescription drug risk score comprises the highest initial risk scoreadded to the multiplied second highest initial risk score and multipliedthe third highest initial risk score.